Transform your customer service with AI and outsourcing

Artificial intelligence is here, and it’s disrupting many industries and jobs. Customer service teams use AI to triage tickets, improve quality, and provide faster support. 

You could even say that customer service teams “outsource” some of the workload to AI. The reality is that AI and outsourcing are head-to-head in a race that seems only to be gaining speed.

As the use of AI continues to soar, it's intriguing to consider where traditional outsourcing fits into this fast-moving landscape. The interplay between AI and outsourcing is fascinating, with each approach evolving and adapting to the changing needs of industries and customers. 

In this article, we’ll explore the pros and cons of using AI, the differences between traditional support and AI support, and why combining the use of AI with human support is the best path forward. 

Defining AI and outsourcing in support

AI and outsourcing tackle similar problems, but in very different ways.

• AI support: AI support refers to the process of leveraging automated systems such as artificial intelligence, natural language processing (NLP), and chatbots to respond to customer inquiries.
• Outsourcing: Outsourced support refers to leveraging an external team of human support agents to handle some or all of your customer service inquiries.

In both scenarios, you’re looking for additional help serving your customers, whether driven by a lack of internal staff or the need to improve efficiency and response times.

Pros and cons of AI in customer support

Like many business decisions, adopting AI in customer support has advantages and disadvantages. First, let’s look at some of the benefits AI provides.

Advantages of AI in customer support

• 24/7 support: AI enables companies to offer round-the-clock support without hiring additional agents for off-hour shifts. Customers can get simple questions answered no matter what time of the day it is.
• Higher quality responses: AI tools in customer support serve various purposes, including responding to customer inquiries using nearly impeccable grammar. AI bots can even personalize their responses if they can access the necessary customer data. 
• Multilingual support: AI helps international companies provide customer service in multiple languages. This increases customer satisfaction, as customers can interact with your company in their native language, making the support interaction easier and quicker.
• Faster training and onboarding: AI tools can suggest training topics based on the support team’s performance and customers’ needs. HR and onboarding tools are even leveraging AI to answer questions from new hires during the onboarding process.
• Faster response times: Customers want answers fast. Automation can enable faster response times by providing immediate assistance to more common questions. This means support teams can focus on responding to more complex customer inquiries. 

When it comes to AI, it’s not all sunshine and rainbows. Implementing AI in customer support has some challenges and disadvantages.

Disadvantages of AI in customer support (and how to overcome them)

• Less personalization: Automated support is less personal by nature, so keeping humans involved is important. AI might be able to handle some of the simple and common issues independently, but more often than not, AI should be used to help human agents do their jobs, not replace them. Humans should co-write responses with AI or QA the work it produces to maintain an acceptable level of personalization.
• Unable to answer difficult questions: Human conversations are fluid in nature. They can pivot quickly and involve difficult topics that an automated system might not be able to handle. When using AI in support, you should have a plan to A) continuously train and improve the AI system and B) provide an escape hatch to reach a human when AI isn’t solving the customer’s problem. 
• Delayed response when escalating to a human: If AI can’t answer a customer’s question, the response time could be delayed while the inquiry gets routed to the necessary human agent. It’s important to make the escalation seamless and transfer information from the AI system to the human agent. That way, they have all of the previous information that the customer provided.
• Prone to errors: We’ve all heard stories about AI bot failures. There’s an inherent risk when employing an automated system to talk to customers. AI bots are mathematical models trained on vast amounts of data. They don’t have emotional intelligence like humans. At ParterHero, we use both automated QA and human QA to ensure we reduce errors and keep conversations as human as possible. In addition, we enable associates to double-check the responses easily. 

• AI can be fooled: AI is subject to being taken advantage of by scammers and fraudsters. For example, someone could possibly encourage an AI bot to give them special treatment, such as a discount. The AI bots should be prevented from making any offers, and instead, these inquiries should be escalated to a human agent as soon as there are signs of deception.

Combining AI and humans in support

We strongly believe the winning combination for modern support teams is human-centric, with AI and automated systems helping support teams do their jobs. 

Leveraging AI alongside a high-performing team of human agents enables companies to provide personalized, faster, and higher-quality support while maintaining an empathetic and human touch. 

For organizations looking to maximize the benefits of AI in their customer service operations, customized AI consulting from expert firms is essential. Tailoring AI solutions specifically to your business needs can help overcome challenges like less personalization and handling difficult questions more efficiently.

AI and human agents are codependent. AI can’t run without humans overseeing the work and stepping in occasionally. And humans can’t do their best work without the help of AI and automated systems.

Combining AI and human support should be done carefully and strategically. 

Here are some tips for blending these two approaches in customer service.

Clearly define roles

Define where, how, and when you’ll use AI vs. human support so that your team understands how the two will work together. AI should be limited mostly to repetitive, straightforward tasks. 

Assign human agents to more complex, nuanced, or emotionally charged issues that require critical thinking, empathy, and problem-solving skills.

Seamless handoff

Create a seamless flow between the AI systems and humans. If the AI system can’t solve a customer problem, it should automatically escalate the inquiry to a human agent without requiring the customer to repeat the information. 

Customers will be frustrated if their issue is escalated to a human agent and the agent doesn’t have any context or history on their interaction with your AI system. The conversation should flow seamlessly, it shouldn’t feel like a new conversation.

Continuous learning and improvement

Human agents and leadership should be able to report on the performance of your AI systems and feed it insights and additional data so that it’s constantly improving and learning. As your products or services change, customer needs will change, and your automated systems must be able to adapt.

Personalization

Leverage AI to gather data about customers and customer inquiries and ensure that the AI support systems and humans use this data to provide a personalized customer support experience. 

Transparency

Transparency builds trust. Be clear with customers about when they’re interacting with an AI system vs. a human support agent. Provide an escalation path for scenarios when the AI system isn’t doing the job.

Focus on customers

Maintain an empathetic, customer-centric approach. Get feedback from customers on your support performance concerning AI and human support. Most importantly, use this feedback to make changes and improvements.

What will happen to those who don’t adopt AI?

AI is being used across many industries and job functions, even outside of customer support. Whether we realize it or not, we’re using AI every day. Search engines, computers, Voice over IP, and other systems all have some form of AI built in. 

Generative AI has advanced this technology astronomically with the ability to automatically create new content, hold conversations, generate ideas, and more. Failing to adopt AI today is like failing to adopt the Internet in the late 1990s. Today, every business uses the Internet in some form, and soon, every business will be using AI.

Businesses must adapt to changing landscapes, new technologies, and different ways of working, and today, AI is a major part of that. It’s a powerful tool that helps provide faster, higher quality and more affordable service. 

With BPOs, AI and outsourcing go hand-in-hand. Today's best BPOs are experts in AI technology, as they pair human support with AI to create high-performing teams.

The opportunity to adopt AI in business is right now. Delaying or avoiding AI will likely be costly for businesses as they will be behind the companies that have already carefully implemented this new and exciting technology. If your company feels overwhelmed by the customer support workload, it might be time to consider using AI and outsourcing to help.

Conclusion

The most successful businesses today use AI to empower customers and support agents. AI has strengthened self-service support and allowed support teams to do higher-quality work more efficiently. But the key is merging AI and humans for a modern, cutting-edge, world-class customer experience.

PartnerHero has stayed close to the rapid evolution of AI technology in customer support. We’ve implemented AI and trained support teams to use it responsibly and effectively to improve the overall business. Reach out if you’d like to discuss how the combination of AI and outsourcing can level up your business.